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Bounded Rationality and Criminal Investigations

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Bounded Rationality and Criminal Investigations:

Has Tunnel Vision Been Wrongfully Convicted?

Brent Snook and Richard M. Cullen

“Cognition is the art of focusing on the relevant and deliberately ignoring the rest.”

Gerd Gigerenzer and Peter Todd

A substantial portion of judgment and decision making research has led to the conclusion

that using heuristics – simple mental strategies that people use to deal with our uncertain world –

results in erroneous decisions. The message that “heuristics are bad” primarily stems from a

wealth of research showing that human decision-making deviates from idealistic, statistics-based

decision-making processes that strive for optimality (Kahneman, Slovic, & Tversky, 1982;

Nisbett & Ross, 1980). In particular, it has been noted that heuristics ignore apparently relevant

information, whereas the idealistic models are thought to examine everything. The negative

view of heuristics has spread to many domains (see Gilovich, Griffin, & Kahneman, 2002, for

some examples), including criminal investigations where the use of heuristics by police officers

is thought to produce reasoning errors that contribute to criminal investigative failures (e.g.,

Findley & Scott, 2006). One heuristic-like process that is cited frequently as an explanation for

criminal investigative failures is “tunnel vision.” If investigating officers, for example, stop

searching for additional suspects after locating a viable suspect, they may be accused of using

tunnel vision. Despite a complete absence of empirical research on tunnel vision in criminal

investigations, there have been calls to eradicate this mental “virus” (e.g., Cory, 2001; Findley &

Scott, 2006). Specifically, it has been recommended that police officers should avoid using


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tunnel vision by employing more deliberate and careful decision-making strategies. While this

solution is intuitively appealing, its feasibility is questionable given: (1) the constrained context

of criminal investigative decision making; and (2) the processing limitations of the human mind.

In this chapter, we outline a psychological framework called bounded rationality and

illustrate how it applies to investigative decision making. Applying the bounded rationality

perspective involves taking an ecological view of cognition by outlining the actual context where

police officers work and determining whether the heuristics that officers use are efficient and

effective decision-making strategies within that context. In taking an ecological view, we hope

to gain some insight about when and why heuristics are likely to succeed and fail in the criminal

investigative environment. We use tunnel vision as a primary example of how heuristics in

policing have been vilified (see Lerner, 2005, for a more detailed discussion of how police

heuristic-led judgments, are criticized in the criminal justice system). Tunnel vision appears to

consist of a set of heuristics, which are arguably adaptive mechanisms that have evolved in the

mind to allow people to make smart decisions. As with all judgments and decisions, decisions

made at various points in the investigative process are constrained by time, knowledge, and

mental capacity. We believe that it is unrealistic to expect police officers to investigate all

possible suspects, collect evidence on all of those suspects, explore all possible avenues

concerning the circumstances surrounding a crime, search for disconfirming and confirming

evidence of guilt for every suspect, and integrate all of this information to make an “optimal”

decision.

Has Tunnel Vision been Wrongfully Convicted as a Flawed Mental Tool?


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Cases of wrongful conviction are being uncovered at an increasing rate and have

rightfully received much public scrutiny (Huff, 2004; Huff, Rattner, & Sagarin, 1986; Rosen,

1992; Scullion, 2004). Such cases have devastating effects on wrongfully convicted individuals

(see Campbell & Denov, 2004; Grounds, 2004) and allow guilty offenders to go free, thereby

bringing disrepute and public mistrust to the administration of justice. In recognition of the need

to prevent wrongful convictions, the Canadian Federal-Provincial-Territorial Heads of

Prosecutions Committee (hereafter referred to as the FPT Committee) set up a Working Group

on the Prevention of Miscarriages of Justice in 2002 to identify the factors that contribute to

these justice system errors. The mandate of the FPT Committee was to, amongst other goals,

ascertain why wrongful convictions were occurring, how criminal investigations were failing,

how police resources could be used more efficiently, and how to facilitate the timely resolution

of cases. The FPT Committee concluded that criminal investigative failures were sometimes a

function of unethical conduct by investigators who assigned blame to the wrong individuals. In

addition, the FPT Committee concluded that investigators sometimes failed to use best practices

(e.g., having knowledge about recent research on eyewitness identification and testimony, line-

up methods, interviewing and interrogation strategies, jail-house informants, and DNA

technology), and that investigators suffered from tunnel vision. According to the varied

definitions that have been offered, tunnel vision in the criminal investigative context involves:

(1) identifying a primary suspect; (2) searching for information about that suspect; and (3)

ignoring information that might disconfirm that the primary suspect is the culprit, including

information about other plausible suspects.

The FPT Committee provided a series of policy recommendations aimed to eliminate, or

at least reduce, future miscarriages of justice. They recommended that police agencies should


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implement training, screening, and disciplinary policies to deal with unethical conduct; police

officers should be educated on best practices; and that police officers should avoid tunnel vision.

Although we wholeheartedly agree with the first two recommendations, we take issue here with

the last one.

Those who argue that tunnel vision is a cause of wrongful convictions seem to believe

that bad outcomes (the conviction of an innocent suspect) only result from either bad decision-

making processes or bad investigators. But good processes and good investigators can also be

associated with bad outcomes. Heuristics are normally effective and efficient strategies for

handling complex information and drawing conclusions from that information, but in some

instances can lead to error. The heuristics that make up tunnel vision are no exception. For

example, even the most decorated police officer can be led astray by “misleading information”

such as a fabricated eyewitness account (although this would not be known to that officer until

after the fact). And whereas bad (e.g., malicious, indifferent, or “nobly corrupt”) investigators

may indeed be the cause of some investigations going awry, tunnel vision is an altogether

different process.

The recommendation to “avoid,” “correct,” or “prevent” tunnel vision is therefore

premature. Not enough is known about tunnel vision to make such recommendations. More

specifically, such a recommendation is as likely to be ineffective as it is to be effective because:

(1) tunnel vision is an ambiguous concept; (2) there has been no systematic study of the

proportion of successful cases where police officers used tunnel vision; and (3) there has been no

proper evaluation of the contribution of tunnel vision to wrongful convictions. Given that

current complaints about tunnel vision are based on retrospective analysis of investigative fiascos

(Findley & Scott, 2006) and the lack of controlled experimental research on the topic, it is not


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surprising that there is no compelling empirical evidence to support the message that tunnel

vision is a bad decision-making strategy. Indeed, the recommendations to correct tunnel vision

appear to be based on nothing but “bad common-sense reasoning” (see Gendreau, Goggin,

Cullen, & Paparozzi, 2002, for how bad common sense based policy recommendations, as

opposed to those based on empirical evidence, can lead to the implementation of ineffective

policies).

The idea that police officers should be wary of tunnel vision mirrors an ongoing debate in

psychology about human rationality. Policy-makers and researchers who have prematurely

focused upon tunnel vision as a flawed mental strategy might be able to increase the likelihood

of reducing the occurrence of investigative failures by considering the issues that are at the heart

of this debate, particularly the arguments that have been put forth since bounded rationality

theory originated in the 1950s. Consequently, the primary goal of this chapter is to expose

readers to the relatively recent developments in the wider rationality debate and illustrate how

this debate is applicable to the understanding of heuristic-led judgments in criminal

investigations.

We begin with an overview of the rationality debate. Put simply, researchers on one side

focus disproportionately on the instances where heuristics produce errors. These researchers

argue that using heuristics is irrational because heuristics are suboptimal to complex decision-

making models that supposedly define the best possible way to make decisions. The other side

argues that heuristics lead to good decisions. According to this second view, tunnel vision might

be helpful to police officers on a psychological level, for example, by allowing them to focus

their thoughts in a complex investigative environment. We then describe the criminal

investigative environment and argue that it is unrealistic to expect officers to use what are


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commonly referred to as fully rational decision-making models. This will be followed by an

attempt to operationalize tunnel vision using existing heuristics that have been outlined and

tested in the psychological literature.

The Rationality Debate in Psychology

The rationality debate is primarily about whether people make good decisions. Arguably,

the most contentious issue in this debate is about how to best measure good decisions. Over the

years, psychologists have varied the decision-making benchmark between how people perform in

the real world to achieve their goals and objectives (referred to as “rationality1” by Mantkelow,

1999) and whether people live up to normative standards (referred to as “rationality2” by

Mantkelow, 1999). In order to be judged rational2, a person would have to search indefinitely

for endless amounts of information, have knowledge of every relevant aspect, weigh all the

available information according to importance, and finally perform intractable mathematical and

statistical calculations. (Such a person has been called homo economicus, or economic man.) If

rationality is thought to be synonymous with optimality – which has often been the case – then

unbounded models of this sort become the definition of rational thinking. People appear doomed

to be irrational if such an unattainable standard is maintained.

Bounded rationality researchers have challenged the view of the human mind as a

statistical software package (Gigerenzer, 2000; Kahneman & Tversky, 1973; Simon, 1955, 1956)

by arguing that the natural constraints on decision making must be taken into account when

assessing human rationality. These researchers proposed that heuristics are more

psychologically plausible models of human decision making than those that involve a high

degree of information integration and abstract mathematical assignments and calculations. Most


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recently, Gerd Gigerenzer and his colleagues (e.g., Gigerenzer, Todd, & The ABC Research

Group, 1999; Gigerenzer, 2001; Todd & Gigerenzer, 2000) have shown that heuristics are

rational because they work well in natural environments.

We therefore adopt the rationality1 definition, and measure rationality by how well

people make decisions in the real world, where decision making is limited by available time,

information or knowledge, and mental resources.

Historical Developments

While it is generally acknowledged that people use heuristics to make all sorts of

decisions, the debate continues over whether their use leads to good or bad decisions. There

were three especially influential contributions to this debate in the second half of the last century

(see Gilovich & Griffin, 2002; Goldstein & Hogarth, 1997). First, Paul Meehl (1954)

empirically compared the judgments of expert clinicians (which were presumably made with

heuristics) with judgments reached by actuarial models and made two important discoveries.

First, the actuarial methods almost always outperformed the experts. Second, the experts thought

they performed better than they actually did. These two findings inspired further research on

ways that the mind produces convincing but erroneous judgments. This further research

generally supported Meehl’s conclusions (e.g., Goldberg, 1965; Sawyer, 1966) that humans

cannot reason as well as they should be able to.

Nobel Prize winning economist and cognitive scientist, Herbert Simon, refuted this

conclusion because it suggested that humans are irrational. Simon thought that it might be the

definition of rationality that was the problem and not human performance on judgment and

decision-making tasks. Simon is now credited with developing the argument that the level of


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rationality2 suggested by rational choice models was an impractical standard for assessing human

judgment and rationality. Proponents of rational choice models assume that people make

judgments by evaluating the probability of each outcome, determining the utility to be gained

from each outcome, combining these two evaluations, and then choosing the option that offers

the optimal combination of probability and utility (Gilovich & Griffin, 2002). Simon (1955,

1956) was opposed to this classical criterion of full rationality, and proposed the principle of

bounded rationality as a more realistic standard. According to Simon’s view, judgment and

decision making is constrained by the processing limitations of the mind so humans have

evolved to use “simple” strategies that can handle complex information (see also Kahneman,

1973; Miller, 1956). Simon believed that humans are in fact rational considering that they make

decisions under limited mental capacity and within the complexities of our uncertain world. He

compared heuristics to a pair of scissors, where one blade represents the environment and the

second represents the mind. Simon asserted that one must study how the two fit together, like

the blades of the scissors, in order to appreciate how heuristics work.

The third important contribution to the rationality debate was the inception of Bayesian

statistical analyses, a form of probability calculus, into the field of psychology by Ward Edwards

(Edwards, Lindman, & Savage, 1963). The Bayesian models set a normative standard that

heuristic-led judgments could be compared to (e.g., Edwards, 1968). Normative standards are

those that establish how things should or ought to be, which things are good or bad, or which

actions are right or wrong. Through such comparisons, it appeared that heuristic-led judgments

were less than optimal because people never performed the way they ought to according to the

idealistic benchmarks. An interest in the causes of this shortcoming subsequently emerged, as


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well as interest in determining ways to correct the apparent “flaws” of human cognition

(Gilovich & Griffin, 2002).

Heuristics and Biases

Following these developments, Daniel Kahneman and Amos Tversky published a series

of papers about how heuristics can sometimes lead to errors and biases (e.g., Kahneman &

Tversky, 1972, 1973; Tversky, 1972; Tversky & Kahneman, 1971, 1973; 1974; 2002). A

collection of their works, along with articles of other like-minded researchers, appeared in a now

classic book titled Judgment Under Uncertainty: Heuristics and Biases (Kahneman, Slovic, &

Tversky, 1982). Its main message is that people often use heuristics rather than fully rational

models to make judgments under uncertainty. The contributors proposed that heuristics can

yield both good and bad decisions, challenged whether complex normative models of human

judgment accurately described underlying mental processes, and attempted to explain the range

of observed human errors as the systematic result of cognition without implying that humans are

irrational (Gilovich & Griffin, 2002). This program of research became known as the “heuristics

and biases” program.

They discovered that everyday judgments do not adhere to the laws of probability or to

statistical principles and argued that the underlying processes in decision making were altogether

different than those implied by rational choice models. They subsequently proposed that people

employ a limited number of simple cognitive rules, or heuristics, that evaluate the likelihood of

options using basic computations that the mind can perform. They proposed three judgmental

heuristics – the representativeness heuristic, the availability heuristic, and the anchoring and

adjustment heuristic – that are commonly used to estimate probabilities, frequencies, and values,


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are cognitively cheap, and are usually effective (see Chapter 2 of this book for a discussion of

how these heuristics have been observed in criminal investigative failures). Heuristics were

defined as any automatic or deliberate strategy that uses a natural assessment in order to estimate

or predict something. The representativeness heuristic, for instance, involves the classification

of things based on how similar they are to a typical case. It is supposedly used when trying to

determine the probability that object A belongs to class B. The subjective probability judgment

rests on how representative object A is of class B. To use a criminal investigative example,

when inferring whether a particular person is likely to be guilty, police officers might mentally

compare the suspect to their perception of a prototypical offender. If the suspect does not show

remorse, for example, a police officer might be inclined to believe the suspect is guilty (see

Weisman, 2004, for a discussion of how showing remorse is interpreted by officials in the

criminal justice system).

Kahneman and Tversky argued that biases occur because heuristics denote a tendency to

make a choice that is inaccurate. For instance, the representativeness heuristic could yield an

incorrect judgment if a suspect did not show remorse but was actually innocent, because a lack

of remorse may not always indicate guilt (an innocent suspect might not show remorse). It was

the tendency for different people to make remarkably similar errors on similar tasks, relative to

the normative models, that led to the conceptualization of the three aforementioned judgmental

heuristics. The predictability of the biases invoked research into the cognitive mechanisms that

caused them – heuristics. However, the biases continued to receive most of the scholarly

attention in the immediate years to follow. Although it was apparently not Kahneman and

Tversky’s intention (see Gilovich & Griffin, 2002), the disproportionate focus on the instances

where heuristics lead to error, rather than the instances where they lead to good decisions,


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combined with the continued scholarly acceptance that normative models were the most superior

method of making decisions, appears to have produced the belief that heuristics are bad, a belief

that still exists today. A negative image of human cognition was thus cast and the “cognitive

miser” image was born (Fiske & Taylor, 1991). According to this image, humans are thought to

deliberately sabotage their own accuracy by using heuristics because they are too lazy (or cheap)

to carry out extensive computational processes. Research illustrating the fallibility of heuristics

has now gained a strong foothold in many areas, including economics, medicine, politics, sports,

and justice (see Myers, 2002, and Piattelli-Palmarini, 1994, for a list of the many documented

heuristic-led biases).

The ABCs of Bounded Rationality

In recent years, Gigerenzer and his colleagues (e.g., Gigerenzer et al., 1999; Gigerenzer

& Selten, 2001; Gigerenzer & Todd, 1999; Todd & Gigerenzer, 2003) at the Centre for Adaptive

Behavior and Cognition at the Max Planck Institute for Human Development (hereafter referred

to as the ABC Research Group) have been challenging the unbalanced view that heuristics are

bad. Gigerenzer and Todd (1999) claim there is an unquestioned assumption in much of

psychology “that the more laborious, computationally expensive, and nonheuristic the strategy,

the better the judgments to which it gives rise” (p. 20, italics added). Those who compare human

reasoning to the unrealistic benchmarks set by rationality2 promote this “more-is-better

ideology.” The ABC Research Group do not believe that more is always better; in fact, they

have argued that less is more in certain situations (Goldstein & Gigerenzer, 1999, 2002; Todd &

Gigerenzer, 2003). In a compilation of their experimental findings and theoretical essays, titled

Simple Heuristics that Make us Smart, Gigerenzer et al. (1999) maintain that the image of


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humans as irrational, resulting from years of comparing human rationality to normative models,

can be mended by considering the real and inherently uncertain environments in which people

make decisions. Essentially, the ABC Research Group maintains that heuristic reasoning

strategies have evolved over time not as suboptimal decision-making strategies, but as effective

strategies that we can use to make everyday judgments and decisions in a complex world.

Two of the ABC Research Group’s core concepts – bounded rationality and ecological

rationality – capture their central ideas. Bounded rationality originated with Simon’s (1955,

1956) notion of satisficing, which involves the mental or physical search through a series of

alternatives until one is found that meets a certain pre-defined level – called the aspiration level.

If you were searching for a house, for instance, you may decide you want a clean house in a

suburban area that is below $300,000. It is possible that you would satisfice when choosing a

house to buy because it is near impossible to look at all available houses everywhere and then

select the best option. This means you would probably buy the first house that met your

aspiration level.

Fundamental to the ABC Research Group’s bounded rationality theory, and the most

intriguing contribution to the ongoing debate about the validity of heuristics, is a metaphor which

views the mind as an adaptive toolbox. Like a carpenter’s toolbox, the mind is equipped with a

repertoire of simple mental tools that are specially suited for certain judgments and decisions.

These mental tools are fast and frugal heuristics that have evolved to allow people to make smart

decisions. The heuristics are fast because they do not involve much calculation or integration of

information, and frugal because they ignore some of the available information, thus sparing

mental resources.


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The simplest tool in the adaptive toolbox is the recognition heuristic, which leads people

to choose something they recognize over something they do not recognize (Goldstein &

Gigerenzer, 1999). As an example of how the recognition heuristic might be used to make a

decision, consider this question: Which of these two National Hockey League players has

achieved the highest total career points – Mark Messier or Eric Cairns? If you only recognize

one player and not the other, you will use the recognition heuristic. Did you choose Mark

Messier? Was it because you recognized Messier and not Cairns? If so, you made a correct

inference by using the recognition heuristic (see Snook & Cullen, 2006). Given a set of options,

the heuristics in the adaptive toolbox specify how people search through the attributes that are

associated with the options, stop that search, and then make a choice. From this toolbox

perspective, human decision making is adaptive because the mind is equipped with heuristics

that meet the demands of a variety of decision tasks.

Ecological rationality is concerned with the structure and representation of information

in the environment and how well heuristics match that structure. To the extent that such a match

exists, heuristics allow people to make an accurate decision quickly (i.e., the heuristic is

ecologically rational). By focusing on the match between the environment and the mind, the

ABC Research Group have placed human reasoning into an evolutionary framework that is

omitted from most decision-making theories. They do not define errors by how far the outcome

and process deviate from rules specified by rational choice models. By contrast, they consider

the ecological rationality of a strategy to assess whether it is effective in a particular situation.

To continue with our hockey player example, the recognition heuristic is ecologically rational for

this particular decision because good hockey players are more recognizable than bad hockey

players. In addition to receiving media attention for being a good player, Messier also received


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wide media exposure through his endorsement of Lays Potato Chips. Of course, Lays would not

have hired an unrecognizable player in the first place. Essentially, people are able to capitalize

on the fact that media exposure is a reflection of hockey greatness because the best players

receive relatively more media exposure, and thus have a greater likelihood of being recognized.

Bounded rationality is based on the premise that our minds construct simplified models

of the complex world in order to deal with uncertainty. The performance of these heuristics has

been compared to complex methods in a series of studies. In perhaps the most comprehensive

study, Czerlinski, Gigerenzer, and Goldstein (1999) compared the performance of simple

heuristic models against multiple regression – a complex statistics-based model – in 20 different

decision environments (e.g., predicting average attractiveness ratings of famous men and

women). They found that the heuristic models provided an equally good fit to a range of data

sets and tend to do so with fewer cues (i.e., they are more frugal). Similar results have been

reported by Dhami and Harries (2001) in their study of how a group of general practitioners

would decide to prescribe blood pressure medication, by Snook, Taylor, and Bennell (2004) in

their study of how people predict offender home locations, by Dhami (2003) in her study of how

judges make bail decisions, and by Smith and Gilhooly (2006) in their study of practitioners’

decisions to prescribe anti-depressant medication. Taken together, these studies have shown that

the fast and frugal heuristic models provide a psychologically plausible account of how people

make all sorts of judgments and decisions.1

1 Other researchers have also suggested that research on cognitive accomplishments has been

“crowded out” by research on cognitive errors, and that statistical analyses typically focus on bias to the exclusion of accuracy. Krueger and Funder (2004), for example, argue that many “biases” can be beneficial and that when an analysis stops without asking “why” such a behavioural or cognitive tendency exists, or what general purpose it might serve, the development of integrative theory and sensible advice is stymied.


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In sum, the rationality debate has a long history and is deeply entrenched in the field of

psychology. Some researchers examine rationality by comparing human reasoning to lofty

benchmarks that they believe people ought to achieve and, because people fall short of these

normative benchmarks, conclude that cognition is flawed and people are unavoidably irrational

(see Kahneman, Tversky, & Slovic, 1982; Piattelli-Palmarini, 1994). The natural response to

this observed “irrationality” has been to prescribe corrective procedures to allow people to get

closer to the benchmark. By contrast, the bounded rationality perspective is concerned with

describing how decision-making strategies allow people to function in the real world. Bounded

rationality researchers use ecological standards (accuracy, speed, frugality), rather than

normative standards, to evaluate human rationality. By considering the nature of the situation in

which a decision is made, it is possible to gain an understanding of when and why a particular

heuristic is likely to succeed or fail in that situation.

Components of the rationality debate are clearly evident in the recent criminal justice

literature that cites tunnel vision as a flawed mental process that produces criminal investigative

failures. The basis of the specific arguments that tunnel vision is a mental virus is the same as

that for the argument that heuristics lead to poor decisions – these strategies are too simple or

they ignore information. Furthermore, in the current concern about tunnel vision, as well as in

the broader debate, there has been a recognized need for corrective measures against heuristic

use. Because the bounded rationality perspective has provided some insight for the greater

rationality debate, it can also shed light on the way tunnel vision is currently viewed by criminal

justice professionals.



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Police officers work in an environment where they are expected to be fully rational.2 This

is especially the case when investigative failures come under direct public and legal scrutiny.

When searching for suspects or through information about a set of existing suspects, police

officers are expected to investigate all possible evidence and all possible suspects, explore all

possible avenues concerning the circumstances surrounding a crime, search for disconfirming

and confirming evidence, and make an optimal decision based on the information found (Forst,

2004; Goff, 2001; Innes, 2002). These expectations are similar to those placed on human

decision making by proponents of rational choice models that assume that people have infinite

time and ability to acquire and process all the information relevant to a particular decision. As

previously mentioned, setting implausible information processing expectations can lead to the

conclusion that the decision maker, in this case the police officer, is irrational, lazy, or used a

flawed mental strategy. In other words, the expectation of optimal processing makes it seem like

police officers are not doing their jobs properly.

According to the bounded rationality perspective, however, people always use heuristics

to make decisions. To apply the bounded rationality framework to police decision making, one

must consider whether a particular heuristic meets the demands of the criminal investigative

environment.

The Bounded Investigative Environment and the Mind

The criminal investigative environment can be best characterized as a naturalistic

decision setting. Such settings typically involve time pressures, high stakes, experienced

decision-makers, inadequate (e.g., missing or uncorroborated) information, ill-defined goals,

2 Or at least parrot the overtones of full rationality (Lerner, 2005).


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poorly defined procedures, stress, dynamic conditions, team coordination, interruptions,

distractions, noise, and other stressors (see Klein, 2001; Orasanu & Salas, 1993). When a crime

is reported, police officers begin a search for information to identify and locate a primary suspect

through physical (e.g., canvassing, interviewing witnesses), mental (e.g., linking related cases),

and/or archival (e.g., searching police files) sources (de Poot & van Koppen, 2004; Sanders,

1977; Innes, 2002).3 In a world without limits, an officer could conduct an infinitely large search

of all information available in the universe. In reality, however, police officers do not have the

luxury of unlimited search time. There are limitations, for example, on how many houses can be

canvassed, how much comparative analysis can be done, and how much effort can be spent

searching police records.

Criminal cases become harder to solve with time (Keppel & Weis, 1994; Mouzos &

Muller, 2001), so many investigations are a race against the clock. Time, therefore, is the first

major constraint on police decision making. Time constrains the search for information by

influencing how resources are allocated, most notably the manpower required to manage

investigative teams, interview witnesses, interact with other agencies, organize information

coming into the investigation, respond to the media, and follow lines of inquiry (Eck, 1979).

Police officers simply do not have time to search for all information that is relevant or necessary

to make an optimal decision. In the end, time-limited searches influence the quality and quantity

of information that is collected, organized, and processed.

The resources that are available during an investigation are also limited. Resource

allocation in a police agency must be prioritized to ensure that all important functions of the

agency continue to operate properly. There are limited financial resources available, and a

3 See Maguire (2003) and de Poot and van Koppen (2004) for a discussion of how different types

of crimes demand different search strategies that vary in complexity.


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balance must be struck between, for example, personnel (e.g., overtime), equipment (e.g.,

radios), and new technology (e.g., forensic capabilities). Although agencies can sometimes

obtain new resources at the start of a major investigation, these cannot be sustained indefinitely.

As with time, resource limitations constrain the search for information that is used to make

investigative decisions.

Similarly, there are limitations on cognitive ability, or constraints on the mental

processing of information (e.g., Kahneman, 1973; Miller, 1956), that limit the decisions made by

investigators. At the most basic level, information processing involves encoding, storing, and

recalling information (Atkinson & Shiffrin, 1968). In order for relevant and novel information to

be encoded and stored in the first instance, one must pay attention to that information. If

attention is interrupted, by distraction for example, the encoding process can be disrupted and the

information will not become stored in memory. In addition to inattention, there are a range of

other limitations on information processing. For example, people can only hold an average of

seven pieces of information in their short term, working memory store at any given time

(Baddeley, 1992; Miller, 1956). The human mind, therefore, does not have the capacity to

consider every piece of information, weight the importance of each piece of information, and

integrate the information in a computationally expensive way. It is unrealistic, then, to expect a

police officer’s mind to act like a computer processor.

Nor should we expect police officers to have unlimited knowledge about every aspect of

criminal investigations or have access to all of the information that is required to make a perfect

decision. It is clearly impossible for police officers, or anyone else for that matter, to be fully

familiar with, aware of, or completely understand criminology, forensics, psychology, law,

biology, sociology, anthropology, linguistics, chemistry, statistics, ethics, politics, management,


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and other areas that could be required to effectively investigate crimes. Knowledge is gained

through experience or study. Police officers accumulate their criminal investigative knowledge

through experience gained from working a range of different cases, through training and self-

study, and by interacting with and listening to other investigators.

The decisions detectives reach are also contingent upon both the quantity and the quality

of information about the current investigation. Police officers, for example, may have only one

eyewitness account of a crime, but must use that limited, and often ambiguous, information to

make investigative decisions (see Manning, 1977; Sanders, 1977). Even if numerous

eyewitnesses come forward, the knowledge they provide is still limited by the fallibility of

human memory (Sporer, 1996).

In addition to the four major constraints, police officers experience pressure from internal

and external sources that can influence the types of decision-making strategies that work well in

the investigative environment (Findley & Scott, 2006; Maguire, 2003). For example, Crego and

Alison (2004) conducted electronic focus groups with 28 senior investigating officers (SIOs) in

the United Kingdom for a range of different types of serious inquiries (e.g., child abductions,

stranger rapes). The officers reported the types of issues they believed were important features

of the critical incidents they had managed. Of the wide range of issues the SIOs reported having

to deal with, several of them were identified as placing considerable stress on the inquiry

process. The officers felt pressure because of the consequential nature of the decisions they

make that can affect people’s lives, the complexity of the case, the local community’s concerns,

the involvement and scrutiny of the press, the inability to influence other individuals that can

have an impact on the investigation, the managing of the investigative team, the ever-changing

nature of the investigation, and their belief that they will be blamed for anything that goes wrong.


20

Police are, furthermore, expected to deal with these pressures amid the regular constraints of the

political and legal systems (Lyons & Truzzi, 1991; Goff, 2001; Young, 1996).

Now that the constraints on investigative decision making have been highlighted, it is

necessary to develop a clear definition of tunnel vision in order to determine whether it is likely

to be an effective strategy in the investigative environment.

Tunnel Vision: Narrow-Mindedness or Focused Determination?

In biological terms, tunnel vision refers to a reduced field of vision – as from within a

tunnel looking out – that results from the loss of peripheral vision with retention of central vision

(Williams, 1985). A Google search of “tunnel vision” retrieves over 14 million hits, however,

and a quick scan of these shows that the term is often used metaphorically to describe how

people in a range of domains (e.g., medicine, politics, law, and business) search for information.

Tunnel vision in this sense is generally seen as a negative or undesirable process, as it refers to

the narrow-minded pursuit of evidence that supports a decision that has already been made while

ignoring evidence that may contradict that initial decision. The main argument against tunnel

vision is that some of the ignored evidence may be valid and people should therefore allow their

beliefs to change in accordance with that evidence. Like the proponents of rationality2, some

criminal justice pundits appear to believe that a different investigative process, involving the

collection and consideration of all available evidence, is superior to this “narrow-mindedness.”

But tunnel vision can also be cast in a positive light; it can be interpreted as an adaptive process

whereby people focus on important, relevant evidence while ignoring evidence that distracts

them from making a decision and acting upon it (Lewicka, 1998). This optimistic view implies

“focused determination,” a desirable human characteristic. Regardless of whether one takes a


21

pessimistic or an optimistic stance, the metaphorical tunnel vision appears to be referring to a

cognitive strategy, albeit an ambiguous one, that guides the search for alternatives and

information.

Tunnel vision has become a convenient catchphrase in the field of criminal justice to

refer to how the police locate suspects and build a case against them. Published articles, books,

and judicial inquiries about wrongful convictions in Canada, such as the Donald Marshall, David

Milgaard, Wilbert Coffin, Steven Truscott (Anderson & Anderson, 1998), Guy Paul Morin

(Anderson & Anderson, 1998; Epp, 1997), and Thomas Sophonow (Anderson & Anderson,

1998; Cory, 2001; Wilson, 2003) cases all cite police or prosecutorial “tunnel vision” as a

contributing factor. In addition, the Canadian Journal of Criminology and Criminal Justice

dedicated a special issue in 2004 to wrongful convictions, and the FPT Committee, discussed

earlier in this chapter, identified “tunnel vision” as one of the contributors to wrongful

convictions.

Although these different published works defined tunnel vision in slightly different ways,

most of the definitions assume that tunnel vision is a form of police misconduct. Even authors

who have attempted to define tunnel vision objectively, by referring to it as the natural way of

processing information that is gathered during an investigation (e.g., Findley & Scott, 2006;

Wilson, 2003), have still cast tunnel vision in a negative light by implying that it is a suboptimal

or flawed investigative strategy. No one appears to have considered that tunnel vision might be a

cognitive strategy that serves a useful purpose for criminal investigators. Below are some of the

definitions that have been provided, which illustrate two things: (1) a lack of agreement about

what exactly tunnel vision is; and (2) the confounding of police misconduct with systematic

cognitive processing.


22

Perhaps the most widely cited definition of tunnel vision is that provided by Justice Cory

in relation to the wrongful conviction of Thomas Sophonow (Cory, 2001). Cory stated that:

Tunnel vision is insidious. It can affect an officer or, indeed, anyone involved in

the administration of justice with sometimes tragic results. It results in the officer

becoming so focussed upon an individual or incident that no other person or

incident registers in the officer’s thoughts. Thus, tunnel vision can result in the

elimination of other suspects who should be investigated. Equally, events which

could lead to other suspects are eliminated from the officer’s thinking. Anyone,

police officer, counsel or judge can become infected by this virus.

Kennedy (2004), a defence lawyer who has assisted with the exoneration of several wrongfully

convicted individuals, argued that “police misconduct, which takes the form of overzealous and

shoddy investigative practices, and specifically “tunnel vision” (p. 200), is the most significant

factor leading to wrongful convictions. To this, Kennedy added:

Tunnel vision can result from incompetence, negligence, or simply a desire to

secure a conviction at any and all costs. It may occur when a police officer,

Crown counsel, or judge believes, prior to the presentation of all the evidence,

that the defendant is guilty… Tunnel vision leads to the use of worthless

evidence, the consideration of erroneous forensic science, and a reliance on the

testimony of jailhouse informants (pp. 200-201).

According to the FPT Committee (2004), tunnel vision is:

the single minded and overly narrow focus on an investigation or prosecutorial

theory so as to unreasonably colour the evaluation of information received and

one’s conduct in response to the information. Tunnel vision, and its perverse by-


23

product “noble cause corruption,” are the antithesis of the proper roles of the

police and Crown Attorney. Yet tunnel vision has been identified as a leading

cause of wrongful convictions in Canada and elsewhere (p. 35).

McFarlane (2004) suggested that tunnel vision occurs when the:

investigative team focuses prematurely, resulting in the arrest and prosecution of a

suspect against whom there is some evidence, while other leads and potential

lines of investigation go unexplored (p. 40).

Findley and Scott (2006) argued that tunnel vision is:

a natural human tendency that has particularly pernicious effects in the criminal

justice system. By tunnel vision, we mean that “compendium of common

heuristics and logical fallacies,” to which we are all susceptible, that lead actors in

the criminal justice system to “focus on a suspect, select and filter the evidence

that will ‘build a case’ for conviction, while ignoring or suppressing evidence that

points away from guilt.” The process leads investigators, prosecutors, judges, and

defence lawyers alike to focus on a particular conclusion and then filter all

evidence in the case through the lens provided by that conclusion. Through that

filter, all information supporting the adopted conclusion is elevated in

significance, viewed as consistent with the other evidence, and deemed relevant

and probative. Evidence inconsistent with the chosen theory is easily overlooked

or dismissed as irrelevant, incredible, or unreliable. Properly understood, tunnel

vision is more often the product of the human condition as well as institutional

and cultural pressures, than of maliciousness or indifference (p. 292).

Martin (2004) stated that tunnel vision is:


24

a set of preconceptions and heuristics that causes police investigators to select

evidence to build a case for the conviction of their chosen suspect while

suppressing or ignoring information and interpretations that point away from

guilt.

Lastly, Wilson (2003) stated that:

We have to remember that wrongful convictions do not happen out of malice. I

have never met a policeman who has deliberately tried to frame an innocent man

– this is not how wrongful convictions occur. Instead, investigators become

convinced of the guilt of people like Mr. Sophonow because the evidence itself

appears to be so convincing. It is crucial to remember that the case against an

accused, on the evidence, can be extremely compelling and yet the accused may

be innocent (p. 5).

Some of these definitions clearly imply police misconduct, as evidenced from the phrase

“noble cause corruption” in the FPT Committee’s report, where a conviction is knowingly

obtained under falsehoods or improper procedures because the police and/or prosecutor believe

the accused to be guilty. By observing in hindsight a case that ended in a wrongful conviction

and noticing that information was ignored during the investigation, it is not surprising that police

misconduct and tunnel vision might be viewed synonymously. Ignoring information certainly

could be the result of either misconduct or tunnel vision. But, it does not necessarily follow that

misconduct is to blame each and every time that an investigator ignores a piece of information.

It is our contention that these are two totally separate concepts that have been confounded.

Whereas malicious investigators may intentionally build a case against a suspect irrespective of

their guilt, detectives using tunnel vision really believe their primary suspect is responsible for


25

the crime. It is this belief that causes them to ignore some information – that which simply does

not register in their thoughts because it does not fit with the story they developed through their

interpretation of the evidence. Or if it does register, it might be “explained away” on the basis of

the investigator’s experience or the other evidence in the case. Tunnel vision, in our view,

guides information search in complex, uncertain, and pressure-filled situations. Ignoring some

information is an integral part of all heuristic strategies. Once it is agreed that misconduct and

tunnel vision are separate processes, we can begin to understand whether tunnel vision is really a

flawed cognitive strategy.

Despite the ambiguity associated with tunnel vision, there have been several

recommendations to remove tunnel vision from the investigative process (Cory, 2001; Findley &

Scott, 2006; FPT Committee, 2004; McFarlane, 2004). Such recommendations and concerns,

however, have been raised despite any compelling empirical evidence that tunnel vision is

maladaptive or even that it can be avoided. This type of recommendation is referred to as

“common-sense” based (Gendreau et al., 2002). Before such policy recommendations can be

implemented with any degree of confidence, they must be validated by systematic research.

Indeed, there are many questions about tunnel vision that remain unanswered. For example, how

often is tunnel vision used? When does tunnel vision lead to good decisions? When does tunnel

vision lead to bad decisions? Why does it work? Why does it fail? How often does tunnel

vision lead to successful criminal investigative outcomes? How often does tunnel vision lead to

criminal investigative failures? Is it realistic to expect the police to follow all lines of inquiry

even if they have a viable suspect identified? How many suspects should the police consider?

When should they stop searching for suspects? How much evidence is required to define a prime


26

suspect? How should police officers choose between equally viable suspects? Perhaps to start

we should ask: What exactly is tunnel vision?

Operationalizing Tunnel Vision

Even though tunnel vision has often been blamed for investigations going awry, the

concept has not been defined in a way that allows it to be meaningfully studied and scrutinized.

Cognitive strategies are normally defined in a way that clearly outlines the step-by-step process

(e.g., an algorithm) that leads to a decision. This has never been done for tunnel vision,

however.4 In this section, we will discuss a number of mental strategies that could potentially

comprise tunnel vision. Each heuristic may serve as a useful function in human cognition – and

in criminal investigations.

Judgment and decision making research provides at least four heuristics that may account

for a portion of the process that is commonly referred to as tunnel vision: (1) the satisficing

heuristic; (2) the take the best heuristic; (3) the elimination-by-aspects heuristic; and (4)

confirmation bias. Satisficing is a heuristic that may potentially be used to guide the search for a

primary suspect by ignoring some of the available information. The next two heuristics, which

also ignore some of the available information, can potentially be used to select a suspect from a

list of known suspects. Each of these three heuristics form part of the adaptive toolbox in the

bounded rationality framework and each involves rules for how to search for information, stop

that search, and make a decision. They have been proposed by bounded rationality researchers

as alternatives to rational2 models. In experiments where decisions made with these models are

compared to decisions made using complex models, the simple models perform at least as well

4 While Findley and Scott (2006) argue that tunnel vision is multidimensional and allude to the

idea that it is made up of heuristics, they draw upon vague cognitive tendencies in their attempt to operationalize tunnel vision.


27

and even better in some situations (e.g., Dhami, 2003, Gigerenzer, 2000). Confirmation bias is

involved during the building of a case against a suspect whom is believed to be the offender.

This is a psychological tendency that occurs when people attempt to support and defend their

decisions, but it can also be viewed as a component of the decision-making process. Arguably,

each of these psychological mechanisms (and other seemingly irrational strategies) serve

adaptive functions in human cognition. Evolutionary psychology maintains that, otherwise,

these mental tools would have been eliminated from our minds.

Satisficing, briefly discussed earlier, is a term that was introduced to the decision making

literature by Simon in the 1950s. It is actually a term that conveniently combines “satisfy” and

“suffice,” and essentially means looking for a good-enough option rather than the best option

when making a decision. The satisficing heuristic involves the sequential consideration of

options until one is found that appears to meet a certain aspiration level. Once that option is

chosen, no further options are considered. Within the context of a criminal investigation,

suspects are usually discovered one at a time and considered in that order. Police officers will

compare all relevant evidence on each suspect to the pre-defined level of evidence that, in the

police officers’ experience, is an indication of guilt. Any suspect that does not meet the

aspiration level is rejected and one primary suspect (the first suspect that meets all the aspiration

levels) emerges. If no suspects meet all the desired levels of evidence, the level of evidence

required may be relaxed and the process repeated, or the suspect who comes closest to the

aspiration level may be chosen. For example, a detective investigating a murder may determine

that the likely offender is a Caucasian male between 18 and 25 years of age, who lives near the

crime scene, has a previous conviction for burglary, and knows the victim. According to the

satisficing heuristic, the first suspect encountered that satisfies all these bits of information (not


28

simply the very first suspect who is encountered) will suffice as the primary suspect and the

search for other suspects is then ceased. In actuality, however, more than one suspect might

meet the aspiration level. Other heuristics might be used to choose the best suspect from that set

of possible suspects.

In the example about purchasing a house that was discussed earlier in this chapter, it can

be seen that satisficing may not always lead to the best possible choice. After you purchase a

house that meets all of your criteria, you may continue to browse the market only to find a better

house with a nicer view than your new home. This is a prime example of the type of situation

that is the basis of the rationality debate. Satisficing is a rational1 strategy that allows us to make

decisions in complex situations where there are so many factors involved that it would be

impossible to integrate them all into a decision. Yet using it might cause one to make a sub-

optimal (irrational2) choice. So a rational strategy produces an apparently irrational result. But,

satisficing allowed the home buyer to reach a good enough decision, which meant that the

process of buying a house could move forward. Therefore, using the satisficing heuristic aided

the achievement of the home buyer’s primary goal. Only in hindsight can it be learned that this

house may not have been the best choice. In criminal investigations, however, the situation is

different. There is a “right answer,” that is, there is normally just one suspect who is responsible

for a crime in question. But police officers probably use this heuristic nonetheless. It involves

setting standards and making sure those standards are met before coming to a final conclusion.

The standards are based on training and experience with similar crimes. This allows

investigators to make a decision and move the case forward. What better strategy is there? If the

evidence points to a suspect, and the police wrongly conclude the suspect is the rightful offender,

this may be an error but it is not an irrational conclusion because the detective followed the


29

evidence. In such a situation, it would be interesting to determine whether other investigators (or

anyone else) would also have followed the same line of inquiry and chosen the wrong suspect.

The take the best heuristic (TTB) makes decisions on the basis of just a few pieces of

data and ignores the rest of the available information (Gigerenzer, 2000; Gigerenzer, Hoffrage, &

Kleinbölting, 1991). The recognition heuristic, described earlier in this chapter, is a simplified

form of TTB in which decisions are based on recognition. Options that are not recognized are

eliminated as potential choices. Recall that the recognition heuristic is only used to make a final

decision when only one option is recognized. In other situations, recognition is used as a

preliminary cue to eliminate some options before additional information is considered.

Informational cues pertaining to the remaining options are then considered in a manner that

involves considering the “best” (most subjectively valid) cue first, then the second best, and so

on, until a cue is found that discriminates between the options.

For police officers assessing whether a case can be built against a suspect, these cues

might include motive, alibi, and prior criminal record, although the specific factors will vary

because there is an element of uniqueness in each case. It is assumed that the list of all potential

suspects is available prior to determining the primary suspect. The police would then evaluate

the motives of the potential suspects, eliminating any who had no motive. They would then do

the same for alibi, then prior criminal record, and other information, until only one suspect

remains. This description of TTB assumes that all cues are binary (present or not present), but

the heuristic can also be generalized in such a way that it considers the values of the cues

(Gigerenzer, 2000) such as the strength of the alibi or the degree of prior criminal activity. In

any case, TTB involves making a decision by only considering enough information to distinguish


30

between options. Some information is simply not used although it may be available, hence TTB

is often referred to by the slightly longer name, “take the best, ignore the rest.”

The elimination-by-aspects (EBA) heuristic, originally proposed by Tversky (1972), is

similar to TTB except that it considers the values of the cues (e.g., degree of prior criminal

activity). The most important piece of evidence is determined, a cut-off value is set, and

suspects are rejected if they do not surpass the cut-off level. This process is repeated with the

second most important piece of evidence, and so on, until only one suspect is left. For example,

the major crime investigator may have four possible suspects and they may all have alibis (which

the investigator believes to be the most important piece of evidence in the case), but one may

have a weaker alibi than the rest. Like TTB, this heuristic does not require considering all pieces

of information when choosing a primary suspect.

Once a primary suspect has been selected, the objective of an investigator is to build a

case against that person for the prosecution. Attempting to find information to support a belief is

commonly referred to as confirmation bias. Confirmation bias, by definition, is a type of

information search strategy whereby people look for information to confirm their beliefs,

theories, or hypotheses, and avoid or misinterpret contradictory evidence so that it does not

disconfirm their beliefs (Arkes & Harkness, 1980; Evans, 1989; Lewicka, 1998; Nickerson,

1998; Wason, 1960). The confirmation bias as it is currently explained in the literature, then,

refers to two separate mechanisms: (1) selective (confirmatory) information search; and (2)

biased interpretation of information (so that it does not disconfirm our beliefs).

Confirmation bias has been called both a “ubiquitous phenomenon” (Nickerson, 1998)

and the primary bias (Klein, 2001). These authors have observed that all people have a tendency

to search for information that confirms their beliefs – a tendency that appears to play a role in


31

many aspects of human cognition. Indeed, the scientific method is designed as an attempt to

overcome confirmation bias – by teaching scientists to seek evidence that disconfirms theories.

Klein (2001), however, noted that one of the most common strategies of scientific research is to

derive a prediction from a theory and show that it is accurate, thereby strengthening the

reputation of that theory. Interviews with prominent and successful NASA scientists (Mitroff,

1974) revealed that a number of them were committed to confirming their theories and saw this

type of strategy as both desirable and necessary. These scientists claim that seeking

confirmatory evidence is necessary for the development and refinement of new theories. Other

researchers have also shown that scientists and other expert professionals do not always search

for disconfirmatory evidence (Greenwald, Pratkanis, Leippe, & Baumgardner, 1986; Haverkamp,

1993; Mahoney & DeMonbreun, 1977). Mahoney and DeMonbreun (1977), for instance,

revealed that the reasoning skills of 15 psychologists and 15 physical scientists (all with PhDs)

did not differ from the reasoning skills of 15 conservative Protestant ministers. When successful

scientists use confirmation seeking strategies, the strategies are perceived as a sign of persistence

or focused determination. Ironically, however, some scientists criticize their research subjects

for using similar strategies on judgment and decision-making tasks.

These arguments can similarly be applied to the criminal investigative context. Officers

who build a successful case by searching for evidence that supports their belief while ignoring

evidence that contradicts their belief would likely be applauded for being persistent, focused,

determined, and dedicated. Those who use the same strategy in a case that ends in a wrongful

conviction, on the other hand, might be accused of using confirmation bias (or perhaps tunnel

vision), as though they neglected to properly fulfill their duties. The confirmation bias is said to

violate the “fully rational” expectation that police officers should search for endless amounts of


32

evidence or falsifying evidence in a totally objective manner, weigh and combine it all, and then

make the best decision. It appears that the outcome of the investigation (rather than how well it

was conducted) is the primary determinant of whether or not the investigative process is

criticized.

If confirmation bias is a conscious strategy, then it should be possible to teach people not

to use it. However, people may seek confirmatory evidence unconsciously rather than

consciously. Mynatt, Doherty, and Tweney (1977, 1978) trained participants on a falsification

technique and an alternate hypotheses technique and found that it did not decrease the prevalence

of confirmatory seeking behaviour when testing hypotheses. The researchers also discovered a

counterintuitive finding – a few participants were actually led astray by the search for

disconfirming evidence (i.e., the falsification technique). Such research suggests that even

individuals who are explicitly trained to make decisions and test hypotheses in a fully rational

manner, using normative strategies, often fail to do so, and training people to use “optimal”

search strategies can sometimes result in worse decisions. Mynatt et al. further found that

promising, but partially incorrect, hypotheses were quickly abandoned when disconfirmation was

received, and participants turned to other hypotheses that were much further from the solution

they were trying to find. So, while searching for confirmatory evidence might increase the

likelihood of supporting a prior belief, it does not completely rule out the possibility that

disconfirmatory evidence might also be discovered.

Tunnel vision appears to consist of a set of heuristics because, by definition, some of the

available information is ignored. There are many documented heuristics that people can use to

search for information, end that search, and make a decision. We have proposed just four that

may comprise the concept of tunnel vision, as currently used in the criminal justice literature, to


33

illustrate the importance of operationalizing concepts in a way that allows them to be empirically

tested. Experimental methods already exist for testing the four strategies we have presented,

whereas tunnel vision appears to be an ambiguous catchphrase that currently cannot be subjected

to the appropriate testing that would be required to determine its actual role in criminal

investigative successes and failures.

Conclusion

In our opinion, there is a gap between the reality of how police officers make decisions

and how the criminal justice system (and the general public) expects them to make decisions.

Given the uncertain, dynamic, and pressure-filled nature of criminal investigations and the

demands of the adversarial justice system, it is not reasonable to recommend that police officers

use “optimal” decision-making strategies. Just like a substantial number of psychological

researchers over the past several decades, those who cite tunnel vision as a cause of wrongful

convictions have made a very important oversight – investigative decisions are made by humans

in the real world, not by supercomputers in some ideal place where time, knowledge, and

resources are unlimited. Decision-making strategies that ignore information, including the

heuristics that comprise tunnel vision, are thus more psychologically and ecologically plausible

than those that strive for optimality.

Unfortunately, policy recommendations to eliminate wrongful convictions by eradicating

mental viruses are not based on any hard facts. Empirical research on the nature of tunnel vision

should be conducted before concluding it causes criminal investigative failures. Comparative

research is required to examine, for example, the prevalence of tunnel vision in criminal

investigations that resulted in both wrongful and rightful convictions. Only then can it be stated


34

with any certainty whether using tunnel vision is a poor way to approach investigative decision

making. Perhaps tunnel vision is used by investigators in every case, but only a very small

percentage of these result in wrongful convictions. This cannot be determined from the present

criminal justice literature because only investigative fiascos have been examined. That is not to

say that the analysis of investigative fiascos is not a useful starting point for identifying the

possible causes of wrongful convictions. Before the apparent use of tunnel vision is used to

drive policy recommendations, however, systematic research demonstrating the role of tunnel

vision in criminal investigative failures is needed.

Ironically, it seems to us that everyone uses tunnel vision, including those who have

argued that tunnel vision is a flawed mental strategy (by presenting only anecdotes that seem to

support their arguments). Some of the authors that we cite seem to have ignored research that

might disconfirm or weaken their arguments. Findley and Scott (2006), for example, made an

argument about tunnel vision that was similar to ours. Like us, they argued that tunnel vision

does not result from malice, and is comprised of heuristic processes. They made their argument

by focusing on the heuristics and biases literature, however, and appear to have ignored, or

perhaps did not search, the bounded rationality literature. The former generally claims that

heuristics are bad, while the latter argues their use can lead to smart decisions. Findley and Scott

then criticize police officers for using tunnel vision and recommend that officers think more

critically when making investigative decisions. This is where our views deviate from that of

many other researchers. By incorporating bounded rationality research into the picture, we have

argued that heuristics, including tunnel vision, might be adaptive processes that allow people to

function in a complex world. According to this view, asking police officers to avoid tunnel

vision might not be a feasible recommendation. Moreover, because tunnel vision helps police


35

officers achieve the positive goal of remaining focused, avoiding tunnel vision may not even be

desirable.

We admit that even we used tunnel vision when we wrote this chapter. Our approach

was to come to a conclusion regarding the use of tunnel vision through our psychological and

legal knowledge and then proceed to construct a rationale for these conclusions by searching for

evidence that supported them. But we were not intentionally trying to mislead anyone when we

chose not to include arguments from some sources. It is simply not feasible to incorporate every

argument that could potentially have an impact on this chapter. We strongly believe,

furthermore, that the bounded rationality approach currently holds the most promise for

understanding human decision making. Of course, if you read this chapter and give it a positive

evaluation, then you will probably conclude that our approach was good, whereas if you do not

agree with our position, you will probably accuse us of being biased. Although we may be

criticized for doing so, we are openly admitting that we used a tunnel vision approach to build

our argument because: (1) our knowledge of this area allows us to believe that we are presenting

a valid argument; and (2) confirmatory strategies have been argued to serve an adaptive purpose

in human reasoning.

In conclusion, the main goal of this chapter is to stop the spread of the idea that heuristics

are inevitably flawed. We recommend that people always consider the positive objectives that

heuristics might serve before concluding that people are irrational, lazy, or mentally inept. We

hope this chapter will help contribute to the larger, ongoing counter-revolution aimed at

balancing the view of the role and value of heuristics in human decision making.


36

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Authors’ Note

Correspondence: Brent Snook, Psychology Department, Science Building, Memorial

University of Newfoundland, St. John’s, Newfoundland, Canada, A1B 3X9. Telephone: (709)

737-3101; facsimile: (709) 737-2430; e-mail: [email protected].

Support for the research reported in this paper was provided to the first author by the

Natural Sciences and Engineering Research Council of Canada, and to the second author by the

Social Sciences and Humanities Research Council of Canada.

Biographies

Brent Snook is an Assistant Professor and Director of the Bounded Rationality and the

Law Laboratory at Memorial University of Newfoundland. He obtained his PhD at the

University of Liverpool, United Kingdom. Brent’s research primarily involves the study of

bounded rationality and the law. He is particularly interested in the types of simple heuristics

that people use to make consequential decisions in legal settings, when and why those heuristics

work succeed and fail, and the conditions under which simple heuristics are used. His research

interests also include pseudoscience in the criminal justice system.

Richard M. Cullen is a graduate student at Memorial University of Newfoundland. He

obtained his BSc (Honours) from Memorial in 2005. His general research interests include

bounded rationality, forensic psychology, and social cognition. Richard’s recent research

involves the development of a model that explains how people form beliefs about investigative

techniques in the absence of compelling empirical evidence. His graduate work involves

studying evidence for the usage of simple heuristics in legal decision making.

bounded rationality and criminal investigations: has ... · pdf filebounded rationality and...

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